title: Serum microRNA expression levels can predict lymph node metastasis in patients with early-stage cervical squamous cell carcinoma.
abstract: Circulating microRNA expression levels can serve as diagnostic/prognostic biomarkers in several types of malignant tumors; however, to our knowledge, there have been reports describing their value in cervical squamous cell carcinoma (SCC). In this study, we used hybridization arrays to compare the microRNA expression profiles in cervical squamous cell carcinomas (SCC) samples among patients with lymph node metastasis (LNM) or without LNM; 89 microRNAs were found to fit our inclusion criteria. Using quantitative PCR (qPCR), we examined the expression levels of these microRNAs in cervical cancer tissue, as well as in serum from patients and healthy women. We compared the expression levels between patients with LNM (n=40) and those without LNM (n=40) and healthy controls (n=20). Using regression analysis, we generated a comprehensive set of marker microRNAs and drew the fitted binormal receiver operating characteristic (ROC) curves to access the predictive value. We identified 6 serum microRNAs that can predict LNM in cervical SCC patients; these microRNAs were miR-1246, miR-20a, miR-2392, miR-3147, miR-3162-5p and miR-4484. The area under the curve (AUC) of the comprehensive set of serum microRNAs predicting LNM was 0.932 (sensitivity, 0.856; specificity, 0.850). The predictive value of the serum microRNAs was inferior to that in tissue (AUC 0.992; sensitivity, 0.967; specificity, 0.950; P=0.018). We compared the LNM predictive value of serum microRNAs and SCC antigen (SCC-Ag) by drawing fitted binormal ROC curves However, serum microRNA analysis is by far superior to serum SCC‑Ag analysis (AUC 0.713; sensitivity, 0.612; specificity, 0.700; P<0.0001). Serum microRNAs are a good predictor of LNM with clinical value in early-stage cervical SCC.
authors.affiliation: Department of Gynecological Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning, Guangxi 530022, P.R. China.
authors.forename: Junying
authors.initials: J
authors.lastname: Chen
authors.forename: Desheng
authors.initials: D
authors.lastname: Yao
authors.forename: Yue
authors.initials: Y
authors.lastname: Li
authors.forename: Hong
authors.initials: H
authors.lastname: Chen
authors.forename: Chanjuan
authors.initials: C
authors.lastname: He
authors.forename: Nan
authors.initials: N
authors.lastname: Ding
authors.forename: Yan
authors.initials: Y
authors.lastname: Lu
authors.forename: Tingyu
authors.initials: T
authors.lastname: Ou
authors.forename: Shan
authors.initials: S
authors.lastname: Zhao
authors.forename: Li
authors.initials: L
authors.lastname: Li
authors.forename: Fengyi
authors.initials: F
authors.lastname: Long
mesh_terms: D014408:Biomarkers, Tumor / Q000097:blood / Q000235:genetics; D002294:Carcinoma, Squamous Cell / Q000097:blood / Q000175:diagnosis / Q000235:genetics* / Q000473:pathology*; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008198:Lymph Nodes / Q000473:pathology*; D008207:Lymphatic Metastasis; D035683:MicroRNAs / Q000097:blood / Q000235:genetics*; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D002583:Uterine Cervical Neoplasms / Q000097:blood / Q000175:diagnosis / Q000235:genetics* / Q000473:pathology*
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs